genome-wide association study (GWAS) approach was proposed to identify loci associated with complex traits without a dependence on prior hypotheses, and became feasible due to the completion of the Human Genome Project in 2001 and subsequent rapid advancements in genotyping technology. In contrast to linkage studies, GWAS can be performed with unrelated subjects, who can be recruited more readily than families, and identifies specific risk alleles. The foundation of GWAS lies in the “common disease, common variant” hypothesis, i.e., that relatively common variants in the population with low penetrance contribute to genetic susceptibility to common diseases (Chakravarti, 1999; Lander, 1996; Pritchard and Cox, 2002; Reich and Lander, 2001). Early GWAS operated under the expectation that the variants underlying complex traits would have moderate-to-large effect sizes and would be detectable in relatively small samples. Although this was true for some phenotypes, such as age-related macular degeneration and exfoliation glaucoma (Haines et al., 2005; Thorleifsson et al., 2007), it has become clear that, for the majority of complex traits, much larger samples are needed to achieve the statistical power necessary to detect the small effects of risk loci. It is now recognized that, for the most part, the risk loci identified could
